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Thesis Proposal Announcement: An Improved Approach of Intention Discovery with Machine Learning for POMDP-based Dialogue Management

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  • Fri, 01/18/2019 - 2:30pm - 4:30pm

An Improved Approach of Intention Discovery with Machine Learning for POMDP-based Dialogue Management

MSc Thesis Proposal by:

RUTURAJ Rajendrakumar RAVAL


Date: Friday, January 18, 2019

Time: 2:30pm - 4:30pm

Location: 9118, Lambton Tower



An Embodied Conversational Agent (ECA) is an intelligent agent that works as the front end of software applications to interact with users through verbal/nonverbal expressions and to provide online assistance without the limits of time, location, and language. To help improving the experience of human-computer interaction, there is an increasing need to empower ECA with not only realistic look of its human counterparts but also a higher level of intelligence. This presentation first highlights the main topics related to the construction of ECA, including different approaches of dialogue management, and then discusses existing techniques of trend analysis for its application in user classification. As a further refinement and enhancement to our prior work on ECA, this thesis research proposes a cohesive framework to integrate emotion-based facial animation with improved intention discovery. In addition, a machine learning technique modeled from Q-learning technique is introduced to support sentiment analysis for automatic adjustment of policy design in POMDP-based dialogue management. It is anticipated that the proposed research work is going to improve the accuracy of intention discover while reducing the length of dialogues.


Thesis Committee:

Internal Reader: Dr. Luis Rueda       

External Reader: Dr. Gokul Bhandari           

Advisor: Dr. Xiaobu Yuan

Christine Weisener
(519)253-3000 ext.3716